In the field of vehicles driven at least in part by a battery powering an electric motor, it is known to monitor certain parameters of the battery to ensure efficient operation of the battery and maintain the “health” of the battery. The State of Health of the battery is a “measure” that reflects the general condition of a battery and its ability to deliver a specified performance compared with a fresh battery. During the lifetime of a battery, the battery performance or “health” tends to deteriorate gradually due to irreversible physical and chemical changes that take place with usage and with age until eventually the battery is no longer usable or “dead”.
As State of Health does not correspond to a particular physical quality, there is currently no consensus on how the State of Health should be determined. The designer of a battery management system may use any of the following parameters (singly or in combination) to define the State of Health of the battery: internal resistance/impedance; capacity; open-circuit voltage; self-discharge; ability to accept a charge; and/or number of charge-discharge cycles.
In order to monitor some parameters of the battery, a current drawn by the battery may be measured and such measurement of the current drawn can be affected by a so-called offset current. The offset current, if not taken into account, can render subsequent estimates of the State of Charge (SoC) of the battery inaccurate. Known SoC estimation techniques that are sensitive to the offset current include simple Coulomb counting techniques and more sophisticated techniques that compare an actual output of the battery to an estimated output (“State Observer” techniques).
A number of offset compensation techniques exist to improve the accuracy of the estimation of the SoC of the battery. However, when the measurement of the current being drawn has a particularly large error, for example due to a faulty current sensor, the most accurate SoC estimation techniques fail to be sufficiently accurate. Such sophisticated techniques also require knowledge of certain physical parameters used to estimate the SoC of the battery, resulting in a requirement for more data and this is computationally expensive.
“Impedance Observer for a Li-Ion Battery Using Kalman Filter” (IEEE Transactions on Vehicular Technology, Vol. 58, No. 8, October 2009, pages 3930-3937) describes the use of an extended Kalman filter in conjunction with a so-called “lumped” model of battery cells in order to estimate the SoC and State of Health (SoH) of a Lithium Ion battery.